assayed_genes = scan("output/gene_list_CD8T.txt",
what = character(), sep="\n")
gene_sets = scan("output/name_s_CD8T.txt",
what = character(), sep="\n")
gene_sets = sapply(gene_sets, strsplit, split=",")
n_genes = sapply(gene_sets, length)
names(n_genes) = NULL
summary(n_genes)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.00 10.75 16.00 14.47 19.00 22.00
## [1] 32
## [1] 1 4 8 9 10 10 10 10 11 11 11 12 12 13 15 16 16 17 17 17 18 18 18 19 19
## [26] 19 19 19 20 21 21 22
alias2Symbol function from
limma.a2s = rep(NA, length(assayed_genes))
for(i in 1:length(assayed_genes)){
gi = assayed_genes[i]
ai = alias2Symbol(gi)
if(length(ai) > 1){
print(gi)
print(ai)
}
a2s[i] = ai[1]
}## [1] "MARS"
## [1] "MARS1" "SLA2"
## [1] "QARS"
## [1] "EPRS1" "QARS1"
## [1] "APITD1"
## [1] "CENPS-CORT" "CENPS"
## [1] "HIST1H2BC"
## [1] "H2BC5" "H2BC4"
## [1] "AIM1"
## [1] "CRYBG1" "SLC45A2" "AURKB"
##
## FALSE TRUE
## 1169 155
##
## FALSE TRUE <NA>
## 70 1099 155
gene_info = data.table(sym_in_data = assayed_genes, sym_limma = a2s)
gene_info[sym_in_data != sym_limma,]## sym_in_data sym_limma
## 1: ZNRD1 POLR1H
## 2: PPAP2A PLPP1
## 3: IMPAD1 BPNT2
## 4: FAM45A DENND10
## 5: C6orf203 MTRES1
## 6: HRSP12 RIDA
## 7: FOPNL CEP20
## 8: WARS WARS1
## 9: CIRH1A UTP4
## 10: RRNAD1 METTL25B
## 11: WDYHV1 NTAQ1
## 12: HIST1H2BD H2BC5
## 13: AGPAT6 GPAT4
## 14: C1orf123 CZIB
## 15: TMEM155 SMIM43
## 16: MARS MARS1
## 17: ENTHD2 TEPSIN
## 18: FAM57A TLCD3A
## 19: HIST1H2AE H2AC8
## 20: QARS EPRS1
## 21: APITD1 CENPS-CORT
## 22: CCDC101 SGF29
## 23: PDDC1 GATD1
## 24: EFCAB4A CRACR2B
## 25: CCDC23 SVBP
## 26: EIF2S3L EIF2S3B
## 27: HIST1H2BC H2BC5
## 28: WRB GET1
## 29: TMEM194B NEMP2
## 30: KIAA0895L MATCAP1
## 31: HIST1H4C H4C3
## 32: HIST1H4J H4C11
## 33: ZNF720 KRBOX5
## 34: FAM49A CYRIA
## 35: FLVCR1-AS1 FLVCR1-DT
## 36: C1orf228 ARMH1
## 37: TTC37 SKIC3
## 38: C9orf114 SPOUT1
## 39: HIST2H2AA4 H2AC19
## 40: HIST2H2BF H2BC18
## 41: C10orf128 TMEM273
## 42: SKIV2L SKIC2
## 43: RNVU1-13 RNVU1-19
## 44: TCTEX1D2 DYNLT2B
## 45: C17orf89 NDUFAF8
## 46: PHBP3 PHB1P3
## 47: SEPT7P7 SEPTIN7P7
## 48: HIST1H2BN H2BC15
## 49: H2BFS H2BC12L
## 50: CASC4P1 GOLM2P1
## 51: LINC00925 MIR9-3HG
## 52: HIST1H3G H3C8
## 53: KLRAP1 KLRA1P
## 54: EFTUD1P1 EFL1P1
## 55: ATP5A1P3 ATP5F1AP3
## 56: CCDC109B MCUB
## 57: ERO1LB ERO1B
## 58: AIM1 CRYBG1
## 59: SELK SELENOK
## 60: C1orf63 RSRP1
## 61: TMEM66 SARAF
## 62: TMEM2 CEMIP2
## 63: PCNXL2 PCNX2
## 64: ACRC GCNA
## 65: PRMT10 PRMT9
## 66: FAM102A EEIG1
## 67: SELM SELENOM
## 68: TMEM57 MACO1
## 69: MKLN1-AS1 LINC-PINT
## 70: RPL9P9 RPL9P8
## sym_in_data sym_limma
gene_info[, gene_symbol := sym_in_data]
gene_info[which(sym_in_data != sym_limma),
gene_symbol := sym_limma]
dim(gene_info)## [1] 1324 3
## sym_in_data sym_limma gene_symbol
## 1: FGR FGR FGR
## 2: ANKIB1 ANKIB1 ANKIB1
## 3: MAD1L1 MAD1L1 MAD1L1
## 4: ICA1 ICA1 ICA1
## 5: NDUFAF7 NDUFAF7 NDUFAF7
## t1
## 1 2
## 1320 2
## sym_in_data sym_limma gene_symbol
## 1: HIST1H2BD H2BC5 H2BC5
## 2: HIST1H2BC H2BC5 H2BC5
## 3: RPL9P8 RPL9P8 RPL9P8
## 4: RPL9P9 RPL9P8 RPL9P8
Gene set annotations (by gene symbols) were downloaded from MSigDB website.
## [1] 1587110 4
## Gene Gene name Cell type nTPM
## 1: ENSG00000000003 TSPAN6 Adipocytes 149.5
## 2: ENSG00000000003 TSPAN6 Alveolar cells type 1 6.1
## 3: ENSG00000000003 TSPAN6 Alveolar cells type 2 10.5
## 4: ENSG00000000003 TSPAN6 Astrocytes 13.9
## 5: ENSG00000000003 TSPAN6 B-cells 1.5
## [1] 79
##
## Adipocytes Alveolar cells type 1
## 20090 20090
## Alveolar cells type 2 Astrocytes
## 20090 20090
## B-cells Basal keratinocytes
## 20090 20090
## Basal prostatic cells Basal respiratory cells
## 20090 20090
## Basal squamous epithelial cells Bipolar cells
## 20090 20090
## Breast glandular cells Breast myoepithelial cells
## 20090 20090
## Cardiomyocytes Cholangiocytes
## 20090 20090
## Club cells Collecting duct cells
## 20090 20090
## Cone photoreceptor cells Cytotrophoblasts
## 20090 20090
## dendritic cells Distal enterocytes
## 20090 20090
## Distal tubular cells Ductal cells
## 20090 20090
## Early spermatids Endometrial ciliated cells
## 20090 20090
## Endometrial stromal cells Endothelial cells
## 20090 20090
## Enteroendocrine cells Erythroid cells
## 20090 20090
## Excitatory neurons Exocrine glandular cells
## 20090 20090
## Extravillous trophoblasts Fibroblasts
## 20090 20090
## Gastric mucus-secreting cells Glandular and luminal cells
## 20090 20090
## granulocytes Granulosa cells
## 20090 20090
## Hepatocytes Hofbauer cells
## 20090 20090
## Horizontal cells Inhibitory neurons
## 20090 20090
## Intestinal goblet cells Ionocytes
## 20090 20090
## Kupffer cells Langerhans cells
## 20090 20090
## Late spermatids Leydig cells
## 20090 20090
## Macrophages Melanocytes
## 20090 20090
## Microglial cells monocytes
## 20090 20090
## Mucus glandular cells Muller glia cells
## 20090 20090
## NK-cells Oligodendrocyte precursor cells
## 20090 20090
## Oligodendrocytes Pancreatic endocrine cells
## 20090 20090
## Paneth cells Peritubular cells
## 20090 20090
## Plasma cells Prostatic glandular cells
## 20090 20090
## Proximal enterocytes Proximal tubular cells
## 20090 20090
## Respiratory ciliated cells Rod photoreceptor cells
## 20090 20090
## Salivary duct cells Schwann cells
## 20090 20090
## Serous glandular cells Sertoli cells
## 20090 20090
## Skeletal myocytes Smooth muscle cells
## 20090 20090
## Spermatocytes Spermatogonia
## 20090 20090
## Squamous epithelial cells Suprabasal keratinocytes
## 20090 20090
## Syncytiotrophoblasts T-cells
## 20090 20090
## Theca cells Thymic epithelial cells
## 20090 20090
## Undifferentiated cells
## 20090
## [1] 602700 5
## Gene Gene name Immune cell TPM pTPM
## 1: ENSG00000000003 TSPAN6 basophil NA 1.2
## 2: ENSG00000000003 TSPAN6 Central memory CD8 T-cell NA 1.7
## 3: ENSG00000000003 TSPAN6 classical monocyte NA 0.2
## 4: ENSG00000000003 TSPAN6 Effector memory CD8 T-cell NA 0.7
## 5: ENSG00000000003 TSPAN6 Exhausted memory B-cell NA 0.7
## Mode NA's
## logical 602700
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.00 0.00 3.10 49.74 27.20 96572.50
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.10 1.70 11.60 67.96 42.80 96572.50
## [1] 30
##
## basophil Central memory CD8 T-cell
## 20090 20090
## classical monocyte Effector memory CD8 T-cell
## 20090 20090
## Exhausted memory B-cell intermediate monocyte
## 20090 20090
## MAIT T-cell Memory CD4 T-cell TFH
## 20090 20090
## Memory CD4 T-cell Th1 Memory CD4 T-cell Th1/Th17
## 20090 20090
## Memory CD4 T-cell Th17 Memory CD4 T-cell Th2
## 20090 20090
## myeloid DC naive B-cell
## 20090 20090
## naive CD4 T-cell naive CD8 T-cell
## 20090 20090
## neutrophil NK-cell
## 20090 20090
## non-classical monocyte Non-switched memory B-cell
## 20090 20090
## Non-Vd2 gdTCR Plasmablast
## 20090 20090
## plasmacytoid DC Progenitor cell
## 20090 20090
## Switched memory B-cell T-reg
## 20090 20090
## Terminal effector memory CD4 T-cell Terminal effector memory CD8 T-cell
## 20090 20090
## total PBMC Vd2 gdTCR
## 20090 20090
## [1] 30 2
## Cell_type Lineage
## 1: Basophil Granulocytes
## 2: Neutrophil Granulocytes
## [1] 1324 3
for(k in 1:length(gene_sets)){
if(length(gene_sets[[k]]) < 5) { next }
print(k)
set_k = paste0("set_", k)
print(gene_sets[[k]])
genes = gene_info[sym_in_data %in% gene_sets[[k]], gene_symbol]
n_genes = sum(genes %in% ct_immune$`Gene name`)
print(sprintf("found %d genes.", n_genes))
if(n_genes == 0) { next }
df = ct_immune[`Gene name` %in% genes,]
dim(df)
df[1:2,]
stopifnot(all(str_to_lower(df$`Immune cell`) %in%
str_to_lower(lineage$Cell_type)))
mat1 = match(str_to_lower(df$`Immune cell`),
str_to_lower(lineage$Cell_type))
df = cbind(df, lineage[mat1,])
df[1:2,]
df$Cell_type = factor(df$Cell_type, levels = lineage$Cell_type)
df = df[df$Lineage != "Total PBMC",]
df$Lineage = factor(df$Lineage,
levels = setdiff(lineage$Lineage, "Total PBMC"))
p1 = ggplot(df, aes(x=Cell_type, y=log10(pTPM + 0.1), fill=Lineage)) +
geom_boxplot() + xlab("Cell type") + ggtitle(set_k) +
theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
scale_fill_brewer(palette="RdBu")
print(p1)
}## [1] 1
## [1] "SPATA6L" "PDCD2L" "MTO1" "GPN2"
## [5] "FGD2" "WRB" "MSH5" "LCAT"
## [9] "RP11-783K16.14" "RP11-493L12.4" "RNU12" "CTB-131B5.2"
## [1] "found 8 genes."
## [1] 2
## [1] "TIMM9" "ABHD11" "IFI44L" "ATG16L2" "BPGM" "BOLA1" "CEP57L1"
## [8] "HDDC3" "MBD5" "CCL3L1" "PGAM4"
## [1] "found 10 genes."
## [1] 3
## [1] "GCFC2" "SLC11A2" "SCPEP1" "FOPNL" "ATF7IP2"
## [6] "MEI1" "TMEM120A" "ZNF511" "PPIAP31" "RP1-134E15.3"
## [11] "TPRG1"
## [1] "found 9 genes."
## [1] 4
## [1] "POLD3" "TTLL1" "REC8" "CDADC1"
## [5] "NR2C1" "TPGS2" "CTSB" "TBCA"
## [9] "RP1-20N2.6" "RP11-446E9.1" "RP11-335G20.7"
## [1] "found 8 genes."
## [1] 5
## [1] "ZNF268" "NSMCE4A" "NDUFAF6" "TMSB15B"
## [5] "CMAHP" "ZNF561" "CCDC23" "ZNF799"
## [9] "ZNF257" "AC098614.2" "AC009403.2" "SF3A3P2"
## [13] "CTD-2555O16.4" "CTD-3092A11.1" "RP11-632K20.7" "RP1-68D18.2"
## [1] "found 8 genes."
## [1] 6
## [1] "C3orf14" "MFSD9" "SCRN2" "XCL1"
## [5] "CCDC28B" "DBF4B" "GNGT2" "DUS1L"
## [9] "NME6" "DLGAP1-AS1" "ENTPD5" "ZNF720"
## [13] "IGHV1-3" "GUSBP9" "AC093642.5" "TRGC2"
## [17] "RN7SL749P" "RP11-1415C14.4" "RPS3AP26"
## [1] "found 12 genes."
## [1] 7
## [1] "RGS1" "TEP1" "IL10" "IFI44" "XRRA1"
## [6] "ZNF683" "TRAV16" "TRAV19" "TRDV1" "TRDC"
## [11] "PATL2" "PTGES3P1" "TRBV3-1" "RP3-395M20.8" "RP11-81H14.2"
## [16] "RP11-23J18.1" "AL161784.1" "RP11-51J9.5"
## [1] "found 12 genes."
## [1] 8
## [1] "CRTAM" "NUDT7" "PLIN2" "CXCR6"
## [5] "EFCAB4A" "KIAA0895L" "PDCL3P5" "RPSAP54"
## [9] "RPL19P12" "RP11-270C12.3" "MIR29B1" "RP11-119F19.2"
## [13] "RPS11P5" "RP11-288E14.2" "EEF1A1P10" "YWHAQP6"
## [17] "RP11-345J4.6" "MIR142"
## [1] "found 5 genes."
## [1] 9
## [1] "CHI3L2" "ZNF302" "GMPR2" "FAHD2A"
## [5] "KHDC1" "ZFP14" "GTSF1" "FAM49A"
## [9] "C1orf228" "CPT1B" "RNU2-2P" "RP11-109G10.2"
## [13] "RP11-247I13.6" "RP11-262H14.3" "ETF1P2" "RN7SL834P"
## [17] "RP11-382J24.2" "RP11-265N6.2" "RP11-1399P15.1"
## [1] "found 10 genes."
## [1] 10
## [1] "PMS2P3" "ASNSD1" "LRRC45" "NAP1L4P1"
## [5] "GEN1" "SLC36A4" "ZNF749" "TRGV10"
## [9] "LINC00630" "ACTG1P10" "CTD-2301A4.3" "WDR86-AS1"
## [13] "ZNF674" "RP11-116B19.2" "RPPH1" "TRAV30"
## [17] "AC006483.1" "RP11-209D14.4" "RP11-686D22.10" "TMEM256P2"
## [1] "found 8 genes."
## [1] 11
## [1] "ZNRD1" "POLR2I" "GALE" "AKR1A1"
## [5] "TRPT1" "GALK2" "C1orf123" "POLR2H"
## [9] "TMEM134" "TREX1" "RP11-33B1.1" "CTD-2521M24.9"
## [1] "found 10 genes."
## [1] 12
## [1] "ZNF85" "CCRL2" "RRNAD1" "SPATA33"
## [5] "RP11-262H14.4" "CES2" "ZNF93" "ARHGAP11B"
## [9] "HIST1H4C" "RP11-545E17.3" "RP11-305L7.3" "FAM200B"
## [13] "RP11-102M11.1" "TPM3P6" "RP11-493L12.6" "AC004158.2"
## [17] "EIF4BP5"
## [1] "found 8 genes."
## [1] 13
## [1] "G2E3" "CHKB" "ARMC2" "CARF"
## [5] "B2M" "ZNF28" "TMSB4X" "RNVU1-13"
## [9] "PIN4P1" "LINC00925" "RP11-467L13.4" "TIPARP"
## [13] "TMEM116" "AC021593.1" "AC008440.5" "MALAT1"
## [1] "found 9 genes."
## [1] 14
## [1] "TNFRSF9" "ZNF585A" "MGAT4A" "TXK" "TCF7"
## [6] "CCR7" "NEK1" "ACRC" "FILIP1L" "GPR183"
## [11] "KRT86" "ANKRD37" "SELL" "MIR4461" "MTND1P23"
## [16] "HCG4P5" "RPL3P2" "RP1-187B23.1" "HLA-W" "RP11-747H7.3"
## [21] "SLC7A5P1" "RP1-313I6.12"
## [1] "found 13 genes."
## [1] 15
## [1] "FOXP1" "RPL21" "AOAH" "RPS14"
## [5] "RP11-572P18.1" "RPL10P3" "RPL9P8" "RPL9P9"
## [9] "CTD-2031P19.4"
## [1] "found 4 genes."
## [1] 16
## [1] "TSPAN32" "HPGD" "KIR3DL1" "NAALADL1"
## [5] "ZNF80" "C10orf128" "TRBV4-2" "TRBV20-1"
## [9] "TRAV12-2" "TRAV24" "RPS19P1" "RP3-340B19.5"
## [13] "KIR2DS4" "AC007041.2" "RN7SL56P" "RNU1-125P"
## [17] "RP11-291B21.2" "RP11-304L19.5" "AC139149.1"
## [1] "found 10 genes."
## [1] 17
## [1] "MBNL3" "GNLY" "VPS8" "ETFDH" "SPIN2B"
## [6] "AC012318.3" "PPIL3" "IER5" "BTBD19" "LINC00944"
## [1] "found 8 genes."
## [1] 18
## [1] "MS4A6A" "SLC41A3" "XCL2" "NFKBIZ"
## [5] "MZT2A" "SLC25A53" "TCTEX1D2" "RP4-742C19.12"
## [9] "GS1-124K5.2" "RP11-254B13.4" "RP11-693N9.2" "AC092580.4"
## [13] "CTB-4E7.1" "USP30-AS1" "HMBS" "CCL3L3"
## [17] "RP11-705C15.5"
## [1] "found 9 genes."
## [1] 19
## [1] "AKAP10" "PUS7L" "NTAN1" "EIF2S3L"
## [5] "ZNF559" "HIST1H4J" "METTL6" "RNVU1-14"
## [9] "TRGV8" "TRGV5" "RPL5P5" "PSMA6P1"
## [13] "MAPKAPK5-AS1" "LINC00426" "RP11-416A17.6" "RP11-713N11.3"
## [17] "RP3-508I15.20"
## [1] "found 9 genes."
## [1] 20
## [1] "CXCL13" "ERO1LB" "HECA" "MAN1C1" "PCNXL2"
## [6] "RASGEF1B" "C1orf162" "NR4A2" "MPZL3" "PLXDC1"
## [11] "CDC42EP3" "PRMT10" "BCL9L" "SELM" "XIST"
## [16] "RPL9P7" "RP11-285F7.2" "PLA2G4B" "ZNF10" "QRSL1P3"
## [21] "KCNQ1OT1"
## [1] "found 16 genes."
## [1] 21
## [1] "DYRK4" "HPS4" "FGFBP2" "DRAM2" "CX3CR1"
## [6] "ADPRM" "HARBI1" "FCRL6" "EFCAB7" "TRAV14DV4"
## [11] "KANSL1-AS1" "RP11-2F9.3" "AC090804.1" "RP4-728D4.2" "ZBTB20-AS1"
## [16] "TRAV1-2" "KLRAP1" "NPM1P5" "PLAC8"
## [1] "found 12 genes."
## [1] 22
## [1] "RP3-324O17.4" "NHP2P1" "MDGA1" "DTD2" "ZBTB8OSP2"
## [6] "RPS2P4" "FLVCR1-AS1" "TRAV8-2" "RP11-12M9.4" "RSC1A1"
## [11] "RP4-800M22.1" "RP3-342P20.2" "PRDX3P1" "PA2G4P4" "SNRPEP4"
## [16] "ADH5P4" "Z97634.3" "RP11-32B5.1" "RP11-90P5.2" "HMGB1P24"
## [21] "MIR3661"
## [1] "found 4 genes."
## [1] 23
## [1] "OAS1" "ELMOD3" "RSAD2" "TMEM138" "ISG20" "TMEM194B"
## [7] "CRYZL1" "TSTD1" "PTGES3P2" "TSC22D3"
## [1] "found 9 genes."
## [1] 24
## [1] "VPS41" "GALK1" "STYXL1" "FUOM" "TECPR1"
## [6] "TRAV8-3" "RNU2-63P" "TRGV2" "AC144530.1" "PVT1"
## [11] "AC013269.1" "CPQ" "HS6ST1"
## [1] "found 9 genes."
## [1] 25
## [1] "IFI27" "RPL21P8" "WDR53" "TRAV35"
## [5] "RP4-694B14.5" "RP11-247I13.3" "CALM2P3" "RP1-182O16.1"
## [9] "CTA-217C2.1" "RP11-381O7.6" "AC147651.4" "AP000476.1"
## [13] "RP11-168J18.6" "KB-1507C5.2" "TRAV1-1" "RP11-613F22.5"
## [17] "CTB-31O20.3" "CTD-3214H19.4" "RP11-297D21.4"
## [1] "found 3 genes."
## [1] 26
## [1] "TM7SF3" "ADAT1" "WDR91" "C12orf57"
## [5] "FAM45A" "SLC37A3" "TNFRSF18" "TRBV9"
## [9] "TRAV13-1" "RP11-773D16.1" "SKP1P1" "INSL3"
## [13] "TRGV7" "SNORD3A" "FAM102A"
## [1] "found 10 genes."
## [1] 27
## [1] "ICA1" "ERMARD" "RNF207" "TNFAIP8L2"
## [5] "CADM1" "TRAV29DV5" "UBA52P6" "ARPC3P1"
## [9] "ZNF826P" "RP5-1099D15.1" "SNRPGP10" "BHLHE40-AS1"
## [13] "RP11-712B9.2" "AP000462.1" "RP11-638I2.10" "RP11-1012A1.7"
## [17] "AC006129.4" "ARL4A"
## [1] "found 7 genes."
## [1] 28
## [1] "ANKIB1" "TMEM66" "NPIPB3" "NPIPB4" "MTND2P28"
## [6] "CTD-2328D6.1" "NPIPB5" "MTATP6P1" "RP11-72I8.1" "RP11-78A19.3"
## [1] "found 5 genes."
## [1] 31
## [1] "RAD51C" "STMN1" "TXNDC17" "TMEM155" "WEE1" "UBE2C" "TYMS"
## [8] "SESTD1"
## [1] "found 8 genes."
## [1] 32
## [1] "CD84" "TRANK1" "SH2D1B" "PET100"
## [5] "AC104820.2" "STAT4" "FAM177A1" "MKLN1-AS1"
## [9] "RP11-373L24.1" "RP11-138A9.2"
## [1] "found 6 genes."
## used (Mb) gc trigger (Mb) limit (Mb) max used (Mb)
## Ncells 4141885 221.3 8075322 431.3 NA 8075322 431.3
## Vcells 20538860 156.7 35549985 271.3 65536 29492531 225.1
## R version 4.2.3 (2023-03-15)
## Platform: aarch64-apple-darwin20 (64-bit)
## Running under: macOS Ventura 13.4.1
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] stringr_1.5.0 limma_3.54.2 tidyr_1.3.0 ggpubr_0.6.0
## [5] ggplot2_3.4.2 data.table_1.14.8
##
## loaded via a namespace (and not attached):
## [1] Rcpp_1.0.10 png_0.1-8 Biostrings_2.66.0
## [4] digest_0.6.31 utf8_1.2.3 R6_2.5.1
## [7] GenomeInfoDb_1.34.9 backports_1.4.1 stats4_4.2.3
## [10] RSQLite_2.3.1 evaluate_0.20 httr_1.4.6
## [13] pillar_1.9.0 zlibbioc_1.44.0 rlang_1.1.0
## [16] rstudioapi_0.14 car_3.1-2 jquerylib_0.1.4
## [19] blob_1.2.4 R.oo_1.25.0 R.utils_2.12.2
## [22] S4Vectors_0.36.2 rmarkdown_2.21 labeling_0.4.2
## [25] RCurl_1.98-1.12 bit_4.0.5 munsell_0.5.0
## [28] broom_1.0.4 compiler_4.2.3 xfun_0.39
## [31] pkgconfig_2.0.3 BiocGenerics_0.44.0 htmltools_0.5.5
## [34] tidyselect_1.2.0 KEGGREST_1.38.0 GenomeInfoDbData_1.2.9
## [37] tibble_3.2.1 IRanges_2.32.0 fansi_1.0.4
## [40] crayon_1.5.2 dplyr_1.1.2 withr_2.5.0
## [43] R.methodsS3_1.8.2 bitops_1.0-7 grid_4.2.3
## [46] jsonlite_1.8.4 gtable_0.3.3 lifecycle_1.0.3
## [49] DBI_1.1.3 magrittr_2.0.3 scales_1.2.1
## [52] cli_3.6.1 stringi_1.7.12 cachem_1.0.7
## [55] carData_3.0-5 farver_2.1.1 XVector_0.38.0
## [58] ggsignif_0.6.4 bslib_0.4.2 generics_0.1.3
## [61] vctrs_0.6.2 RColorBrewer_1.1-3 org.Hs.eg.db_3.16.0
## [64] tools_4.2.3 bit64_4.0.5 Biobase_2.58.0
## [67] glue_1.6.2 purrr_1.0.1 abind_1.4-5
## [70] fastmap_1.1.1 yaml_2.3.7 AnnotationDbi_1.60.2
## [73] colorspace_2.1-0 rstatix_0.7.2 memoise_2.0.1
## [76] knitr_1.44 sass_0.4.5